Labeling is one of the techniques in image signal processing for distinguishing different objects in an image. Labeling assigns a unique number to each object in an image that contains a plurality of objects. A specific object of interest is then processed using the object's unique number. The labeling technique has various applications in image processing. For example, in a facial recognition system for access control, the labeling technique detects and isolates a facial area in an image obtained by an optical device. The labeling technique and a technique for detecting a specific object in an image using labeling may also be used in iris recognition, recognition of a specific part of the human body, or a defect detection in automated manufacturing.
Conventionally, labeling uses either an iterative algorithm, an algorithm using one or more loops, recursive calls or a stack structure. A labeling algorithm stores information regarding a frame or a line of a desired image into a memory and then uses the stored information. If sufficient hardware resources are available, a conventional labeling algorithm may be used even though it requires a considerable amount of time. However, a conventional labeling algorithm is often impractical mobile equipment designed for portability, convenience, and mobility which typically has limited hardware resources and/or processing capacity, such as, for example, a mobile terminal. Also, facial recognition based on a labeling algorithm, as well as applications in a digital camera using facial recognition, such as, for example, AF (Auto Focus), AWB (Auto White Balance) or AE (Auto Exposure), are difficult to implement with limited hardware resources.
Recently, an interactive video call service has been introduced for entertainment purposes. A mobile terminal with a facial detection function has been developed for such a service, which expands the HCI (Human Communication Interact) technology to mobile terminals. However, such a terminal (a mobile phone, a digital camera, an optical device or a certification system) processes an input image using frame or line information stored in memory, thus requiring large memory resources. Consequently, as the hardware requirements increase, the hardware terminal becomes more expensive. Moreover, as mentioned above, conventional processing is based on memory storage and use of the stored information. Thus, processing time, including data storage and retrieval, also increases.